Version 1.1-0 of the pls package is now available on CRAN.
The pls package implements partial least squares regression (PLSR) and
principal component regression (PCR). Features of the package include
- Several plsr algorithms: orthogonal scores, kernel pls and simpls
- Flexible cross-validation
- A formula interface, with traditional methods like predict, coef,
plot and summary
- Functions for extraction of scores and loadings, and calculation of
(R)MSEP and R2
- A simple multiplicative scatter correction (msc) implementation
- Functions for plotting predictions, validation statistics,
coefficients, scores, loadings, biplots and correlation loadings.
The main changes since 1.0-3 are
- mvr, mvrCv and predict.mvr now has builtin support for scaling of X.
- A new function stdize for explicit centering and/or scaling.
- Correlation loadings plot (corrplot).
- New argument `varnames' in coefplot, to label the x tick marks with the
variable names.
- loadingplot, coefplot and plot.mvrVal can now display legends, with the
argument 'legendpos'.
See CHANGES in the sources for all changes.
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Bjørn-Helge Mevik and Ron Wehrens